26th Australian Institute of Physics Congress and the Australian and New Zealand Conference on Optics and Photonics

Automated Die-Scale Cryogenic Characterization of SiMOS Spin Qubit Devices

Not scheduled

20m

Belinda Hutchinson Building (The University of Sydney )

Poster AIP | Quantum Science and Technology (QST)

Description

Quantum computers are rapidly approaching utility-scale operation, requiring not only high-fidelity qubit control but also scalable and reproducible fabrication. Silicon MOS spin qubits are a compelling platform to meet these requirements, offering compatibility with CMOS technology, a minimal footprint, and state-of-the-art gate fidelities [1]. However, cryogenic characterization is emerging as a critical bottleneck in scaling device development. Conventional approaches relying on wire bonding and manual tuning are low-throughput - characterizing a single device can require days to weeks - making systematic studies of design variations and fabrication process variability impractical. To address this challenge, we combine a die-scale cryogenic probing station [Figure 1a] with a machine learning-based charge state classifier and a fully automated tuning pipeline, achieving a 10-100× improvement in characterization throughput over traditional methods. Using this platform, we demonstrate the automated screening, characterization, and tune-up of 16 double quantum dot (DQD) devices in under 22 hours [Figure 1c]. Of these, 8 devices were tuned to the few-electron (N = 4) regime with reservoir isolation sufficient for further characterization [Figure 1b]. Beyond throughput, this platform enables statistically meaningful design-of-experiment studies, as demonstrated in [2] where systematic trends in tunnel rate controllability are identified as a function of gate geometry variations. These results establish a scalable framework for variability-aware design optimization, statistical benchmarking of qubit performance, and accelerated iteration across fabrication runs - key steps toward manufacturable quantum processors.

Reference list
1. P. Steinacker et al., “Industry-compatible silicon spin-qubit unit cells exceeding 99% fidelity,” Nature, 646, no. 8083, 81–87, (2025).
2. M. Candido et al., "Investigation of 300mm Process SiMOS Spin Qubit Device Uniformity with Automated Cryogenic Probing," IEEE IEDM (2025).